DOIONLINE

DOIONLINE NO - IJAMCE-IRAJ-DOIONLNE-1743

Publish In
International Journal of Advances in Mechanical and Civil Engineering (IJAMCE)-IJAMCE
Journal Home
Volume Issue
Issue
Volume-2, Issue-1  ( Feb, 2015 )
Paper Title
Environmental Impact Assessments Of Heavy Metal On Soil Using Ann Modeling Techniques
Author Name
A. Ganthimathi, A. Anbarasi
Affilition
Associate Professor, Department of Civil Engineering, Kumaraguru College of Technology, Coimbatore - 30 eHead and Associate Professor, Department of MCA Computer Science, Karpagam Institute of Technology, Coimbatore-45
Pages
53-56
Abstract
Artificial Neural Network Model used to predict the Heavy metal in various localities Topsoil samples (0-20cm) were taken at various locations with reference to latitude and longitude. The concentration of heavy metal Fe were analyzed in the Atomic Absorption spectrometer. An artificial neural network technique is used to develop a model to predict the constituents of the heavy metal in the soils such as Mercury, Cadmium, Iron. The developed neural networks consists of 2 input neurons for latitude and longitude, 6 hidden layers consisting of 10 to 20 neurons in each layer for training the data and 1 neuron to predict the constituents of the heavy metal in the soils. Keywords- Heavy Metal, Artificial Neural Network, Soil pollution, Assessment of Heavy metal.
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